Sheared turbulent flows and wake dynamics of an idled floating tidal turbine

Ocean energy extraction is on the rise. While tides are the most predictable amongst marine renewable resources, turbulent and complex flows still challenge reliable tidal stream energy extraction and there is also uncertainty in how devices change the natural environment. To ensure the long-term integrity of emergent floating tidal turbine technologies, advances in field measurements are required to capture multiscale, real-world flow interactions. Here we use aerial drones and acoustic profiling transects to quantify the site- and scale-dependent complexities of actual turbulent flows around an idled, utility-scale floating tidal turbine (20 m rotor diameter, D). The combined spatial resolution of our baseline measurements is sufficiently high to quantify sheared, turbulent inflow conditions (reversed shear profiles, turbulence intensity \u3e20%, and turbulence length scales \u3e 0.4D). We also detect downstream velocity deficits (approaching 20% at 4D) and trace the far-wake propagation using acoustic backscattering techniques in excess of 30D. Addressing the energy-environment nexus, our oceanographic lens on flow characterisation will help to validate multiscale flow physics around offshore energy platforms that have thus far only been simulated

Localised anthropogenic wake generates a predictable foraging hotspot for top predators

Lilian Lieber et al. examined seabird foraging around natural and man-made wakes, finding that wake from a turbine structure generates a more intense and predictable foraging hotspot for seabirds. This shows the importance of changes in physical forcing to top predators when installing or removing offshore structures

Selective foraging behavior of seabirds in small-scale slicks

Lieber L, Füchtencordsjürgen C, Hilder RL, et al. Selective foraging behavior of seabirds in small-scale slicks. Limnology and Oceanography Letters . 2022.Marine predator foraging opportunities are often driven by dynamic physical processes enhancing prey accessibility. Surface slicks are ubiquitous yet ephemeral ocean features where convergent flows accumulate flotsam, concentrating marine organisms and pollutants. Slicks can manifest on the sea surface as meandering lines and seabirds often associate with slicks. Yet, how slicks may influence the fine-scale foraging behavior of seabirds is only coarsely resolved. Here we show that seabirds selectively forage in small-scale slicks. We used aerial drone technology to track surface-foraging terns (Sternidae, 107 tracks) over evolving slicks advected by the mean flow and reshaped by localized turbulence at scales of meters and seconds. Terns were more likely to switch into high-tortuosity foraging behavior when over slicks, with plunge-dive events occurring significantly more often within slicks. As we demonstrate that terns select dynamic slicks for foraging, our approach will also lend itself to interaction studies with pollutants, plumes, and fronts

A physics-enabled flow restoration algorithm for sparse PIV and PTV measurements

The gaps and noise present in particle image velocimetry (PIV) and particle tracking velocimetry (PTV) measurements affect the accuracy of the data collected. Existing algorithms developed for the restoration of such data are only applicable to experimental measurements collected under well-prepared laboratory conditions (i.e. where the pattern of the velocity flow field is known), and the distribution, size and type of gaps and noise may be controlled by the laboratory set-up. However, in many cases, such as PIV and PTV measurements of arbitrarily turbid coastal waters, the arrangement of such conditions is not possible. When the size of gaps or the level of noise in these experimental measurements become too large, their successful restoration with existing algorithms becomes questionable. Here, we outline a new physics-enabled flow restoration algorithm (PEFRA), specially designed for the restoration of such velocity data. Implemented as a 'black box' algorithm, where no user-background in fluid dynamics is necessary, the physical structure of the flow in gappy or noisy data is able to be restored in accordance with its hydrodynamical basis. The use of this is not dependent on types of flow, types of gaps or noise in measurements. The algorithm will operate on any data time-series containing a sequence of velocity flow fields recorded by PIV or PTV. Tests with numerical flow fields established that this method is able to successfully restore corrupted PIV and PTV measurements with different levels of sparsity and noise. This assessment of the algorithm performance is extended with an example application to in situ submersible 3D-PTV measurements collected in the bottom boundary layer of the coastal ocean, where the naturally-occurring plankton and suspended sediments used as tracers causes an increase in the noise level that, without such denoising, will contaminate the measurements

Increasing the Depth of Current Understanding: Sensitivity Testing of Deep-Sea Larval Dispersal Models for Ecologists

Larval dispersal is an important ecological process of great interest to conservation and the establishment of marine protected areas. Increasing numbers of studies are turning to biophysical models to simulate dispersal patterns, including in the deep-sea, but for many ecologists unassisted by a physical oceanographer, a model can present as a black box. Sensitivity testing offers a means to test the models' abilities and limitations and is a starting point for all modelling efforts. The aim of this study is to illustrate a sensitivity testing process for the unassisted ecologist, through a deep-sea case study example, and demonstrate how sensitivity testing can be used to determine optimal model settings, assess model adequacy, and inform ecological interpretation of model outputs. Five input parameters are tested (timestep of particle simulator (TS), horizontal (HS) and vertical separation (VS) of release points, release frequency (RF), and temporal range (TR) of simulations) using a commonly employed pairing of models. The procedures used are relevant to all marine larval dispersal models. It is shown how the results of these tests can inform the future set up and interpretation of ecological studies in this area. For example, an optimal arrangement of release locations spanning a release area could be deduced; the increased depth range spanned in deep-sea studies may necessitate the stratification of dispersal simulations with different numbers of release locations at different depths; no fewer than 52 releases per year should be used unless biologically informed; three years of simulations chosen based on climatic extremes may provide results with 90% similarity to five years of simulation; and this model setup is not appropriate for simulating rare dispersal events. A step-by-step process, summarising advice on the sensitivity testing procedure, is provided to inform all future unassisted ecologists looking to run a larval dispersal simulation

Advancing multi-vehicle deployments in oceanographic field experiments

Our research concerns the coordination and control of robotic vehicles for upper water-column oceanographic observations. In such an environment, operating multiple vehicles to observe dynamic oceanographic phenomena, such as ocean processes and marine life, from fronts to cetaceans, has required that we design, implement and operate software, methods and processes which can support opportunistic needs in real-world settings with substantial constraints. In this work, an approach for coordinated measurements using such platforms, which relate directly to task outcomes, is presented. We show the use and operational value of a new Artificial Intelligence based mixed-initiative system for handling multiple platforms along with the networked infrastructure support needed to conduct such operations in the open sea. We articulate the need and use of a range of middleware architectures, critical for such deployments and ground this in the context of a field experiment in open waters of the mid-Atlantic in the summer of 2015.Advancing multi-vehicle deployments in oceanographic field experimentsacceptedVersio

Data from: Sheared turbulent flows and wake dynamics of an idled floating tidal turbine

Input data (minimally processed ADCP Matlab files) used to generate this study\u27s results. The data is divided into two folders: 1) Broad-scale Transects and 2) Fine-scale Transects and 3), a README file is provided